Is there a good ratio between the positive and negative rewards in reinforcement learning?
It usually does not matter, but I'm sure there are situations where it could matter.  In theory, if a reward for good behavior is higher than the rewards for bad behavior, then the neural network will be trained such that the higher rewards are preferred, even if those higher rewards are negative.  For example, if a bad reward is -100, then a relatively good reward could be -50, and the network will then be more likely to choose the action with -50 reward over the action with -100 reward.